Exploiting Social Networks of Twitter in Altmetrics Big Data

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Exploiting Social Networks of Twitter in Altmetrics Big Data

Type: Article in monograph or in proceedings
Title: Exploiting Social Networks of Twitter in Altmetrics Big Data
Author: Imran M.Akhtar A.Said A.Safder I.Hassan S.U.Aljohani N.R.
Journal Title: STI 2018 Conference Proceedings
Start Page: 1339
End Page: 1344
Publisher: Centre for Science and Technology Studies (CWTS)
Issue Date: 2018-09-11
Keywords: Scientometrics
Abstract: The advent of Web 2.0 brought platform for the internet users to interact, collaborate and share ideas and opinions. These platforms are referred as Social Media platform, which enables all internet users to disseminate information in contrast to certain content providers. This massive diffusion of information by internet users resulted in consummating the term “user generated content” (Lee, 2011). This content coincides with the opinions and interests of different communities present over the social media. A social media community is a network of people connected via social media platform, presumably having similar interests. The researcher and scientific community have actively adopted social media to emulate impact and influence of scholarly literature using Web 2.0 (Priem & Bradely, 2010). Given the recognize need and recent interest of Scientometrics community to tap the advancement of social media platforms to compliment traditional bibliometric based scientific assessments, we explore the behaviour and properties of scholarly community present on twitter. Using the dataset of over 6 million tweets, we examine major commonalities and differences of twitter based social media activity of users across 17 broader disciplines.
Handle: http://hdl.handle.net/1887/65219
 

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